Descriptive Analytics and you can Artwork out-of Commonly used Terms

I checked out prospective variations because of the web site, geographical area, and you will ethnicity playing with t-assessment and you can study from variance (ANOVA) with the LIWC group proportions. On two other sites, half a dozen of a dozen t-testing was indeed tall from the after the categories: first-individual only 1 [t(3998) = ?5.61, p Additional Dining table dos to have means, simple deviations, and contrasts between cultural communities). Contrasts revealed extreme differences between White and all most other cultural organizations within the five of your half dozen extreme ANOVAs. Ergo, i integrated ethnicity since a dummy-coded covariate into the analyses (0 = Light, step one = All other cultural communities).

Of your twelve ANOVA testing associated with geographical part, only a couple of was basically high (friends and self-confident feelings). As variations were not commercially important, i failed to think geographical region when you look at the next analyses.

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Frequency off keyword have fun with is obvious inside descriptive analytics (pick Table 1) and through phrase-clouds. The definition of-cloud approach illustrates by far the most commonly used terminology over the whole attempt and also in each of the age range. The word-cloud program immediately excludes specific terminology, plus blogs (a beneficial, and, the) and prepositions (to help you, with, on). The remaining blogs terms try scaled in proportions in accordance with their volume, starting an user-friendly portrait of the most prevalent blogs terms and conditions around the the latest sample ( Wordle, 2014).

Figure step one reveals the new 20 most commonly known stuff terminology used in the whole attempt. As can rise above the crowd, the essential commonly used terms and conditions was indeed like (appearing within the 67% of pages), instance (appearing when you look at the 62% of users), searching (lookin inside the 55% off users), and you will someone (searching in the fifty% of users). Therefore, the most common conditions was comparable all over age groups.

Shape dos shows the following 31 most common articles terms in the this new youngest and you can eldest a long time. By detatching the initial 20 preferred stuff terms and conditions along side sample, we instruct heterogeneity from the relationship profiles. Within the next 30 words into the youngest age bracket, significant number words integrated rating (36% away from profiles on youngest age group), wade (33% of users regarding the youngest age bracket), and you may works (28% regarding users on the youngest generation). Conversely, the latest earliest age group had highest percent out-of words eg traveling (31% out of pages regarding oldest age bracket), great (24% regarding profiles on the earliest generation), and you will relationship (19% from profiles on the earliest age group).

Second 29 popular terms and conditions regarding youngest and you will earliest age communities (once subtracting brand new 20 most common conditions off Contour step one).

Hypothesis Comparison of age Differences in Vocabulary when you look at the Relationship Profiles

To check on hypotheses, the new portion of terms and conditions in the dating profile that suit for each and every LIWC group offered as based variables within the regressions. We examined age and you will gender due to the fact independent parameters together with changing to own website and you may ethnicity.

Hypothesis step one: Older age could be of increased portion of conditions from the adopting the classes: first-person plural pronouns, family members, family members, fitness, and you will confident emotion.

Results largely offered Hypothesis 1 (see Desk 2). Four of your four regressions revealed a significant head effect to possess many years, in a manner that as the age the fresh reputation author enhanced, the newest part of words on the class improved regarding following the categories: first-individual plural, loved ones, health, and you may self-confident emotion. I receive no tall years impression on proportion of terms throughout the family unit wife Porto seguro members classification.

a Gender: 0 (female) and you will step one (male). b Webpages: The two websites was in fact dictomously coded while the step one and you will 0. c Ethnicity: 0 (White) and you may step 1 (Cultural or racial minority).

a beneficial Gender: 0 (female) and you can step 1 (male). b Webpages: The 2 other sites had been dictomously coded since 1 and you may 0. c Ethnicity: 0 (White) and you can step 1 (Cultural or racial minority).